Patients come from populations and populations contain patients. A two‐stage scientific and ethics review: The next adaptation for single institutional review boards
Bibliographic record
Abstract
INTRODUCTION: For nearly 50 years, institutional review boards (IRB) and independent ethics committees have featured local oversight as a core function of research ethics reviews. However growing complexity in Alzheimer's clinical research suggests current approaches to research volunteer safety is hampering development of new therapeutics. As a partial response to this challenge, the NIH has mandated that all NIH-funded multi-site studies will use a single Institutional Review Board. The perspective describes a joint program to provide a single IRB of record (sIRB) for phases of multi-site studies. METHODS: The approach follows two steps. One, an expert Scientific Review Committee (SRC) of senior researchers in the field will conduct the review principally of scientific merit, significance, feasibility, and the likelihood of meaningful results. The second step will be the IRB's regulatory and ethics review. The IRB will apply appropriate regulatory criteria for approval including minimization of risks to subjects and risks reasonable in relation to anticipated benefits, equitable subject selection, informed consent, protections for vulnerable populations, and application of local context considerations, among others. RESULTS: There is a steady demand for scientific, ethical and regulatory review of planned Alzheimer's studies. As of January 15, 2017, there are nearly 400 open studies, Phase II and III, industry and NIH sponsored trials on disease indications affecting memory, movement and mood in the US. CONCLUSIONS: The effort will initially accept protocols for studies of Alzheimer's disease, dementia, and related disorders effecting memory, movement and mood. Future aims will be to provide scientific review and, where applicable, regulatory and ethical review in an international context outside North America with sites possibly in Asia, Europe and Australia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".